使用tidyquant R遍历参数列表

Question

我有一个数据集，我想使用不同参数值的tq_mutate和rollapply来处理它。

目前，我使用for循环来遍历所有参数值，但我确信这不是完成这项任务的最有效或最快的方法(尤其是当我要查看大量参数值时(。如何改进或删除for循环？我怀疑这意味着使用purrr:：map或其他方式(多线程/多核等(，但我在网上找不到有用的例子。

下面是一些示例代码。请忽略数据集的简单性和比例函数的输出，它仅用于说明目的。我想做的是迭代许多不同的V0值。

library(dplyr)
library(tidyverse)
library(broom)
library(tidyquant)
my_bogus_function <- function(df, V0=1925) { 
# WILL HAVE SOMETHING MORE SOPHISTICATED IN HERE BUT KEEPING IT SIMPLE
# FOR THE PURPOSES OF THE QUESTION
c(V0, V0*2)
}
window_size <- 7 * 24
cnames = c("foo", "bar")
df <- c("FB") %>%
tq_get(get = "stock.prices", from = "2016-01-01", to = "2017-01-01") %>% 
dplyr::select("date", "open")
# CAN THIS LOOP BE DONE IN A MORE EFFICIENT MANNER? 
for (i in (1825:1830)){
df <- df %>% 
tq_mutate(mutate_fun = rollapply,
width      = window_size,
by.column  = FALSE,
FUN        = my_bogus_function,
col_rename = gsub("$", sprintf(".%d", i), cnames), 
V0 = i
)
}
# END OF THE FOR LOOP I WANT FASTER

Answer 1

考虑到R使用一个核心，我发现通过使用并行、doSNOW和foreach包进行改进，这允许使用多个核心(请注意，我在windows机器上，所以其他一些包不可用(。

对于多线程/并行化/矢量化代码，我相信还有其他答案。

这是任何感兴趣的人的代码。

library(dplyr)
library(tidyverse)
library(tidyquant)
library(parallel)
library(doSNOW)  
library(foreach)
window_size <- 7 * 24
cnames = c("foo", "bar")
df <- c("FB") %>%
tq_get(get = "stock.prices", from = "2016-01-01", to = "2017-01-01") %>% 
dplyr::select("date", "open")
my_bogus_function <- function(df, V0=1925) { 
# WILL HAVE SOMETHING MORE SOPHISTICATED IN HERE BUT KEEPING IT SIMPLE
# FOR THE PURPOSES OF THE QUESTION
c(V0, V0*2)
}
# CAN THIS LOOP BE DONE IN A MORE EFFICIENT/FASTER MANNER? YES 
numCores <- detectCores() # get the number of cores available
cl <- makeCluster(numCores, type = "SOCK")
registerDoSNOW(cl) 
# Function to combine the outputs 
mycombinefunc <-  function(a,b){merge(a, b, by = c("date","open"))}
# Run the loop over multiple cores
meh <- foreach(i = 1825:1830, .combine = "mycombinefunc") %dopar% {
message(i)
df %>% 
# Adjust everything
tq_mutate(mutate_fun = rollapply,
width      = window_size,
by.column  = FALSE,
FUN        = my_bogus_function,
col_rename = gsub("$", sprintf(".%d", i), cnames), 
V0 = i
)
}
stopCluster(cl)
# END OF THE FOR LOOP I WANTED FASTER